Technical Field
The present teaching relates generally to methods and system for process sharing between different system platforms. Specifically, the present teaching relates to methods and system for process sharing and communication between different medical imaging system platforms.
Discussion of Related Art
With the large number of applications available on computing devices, there is a need to allow these applications to share with each other data created in different applications. One conventional solution is through a set of interfaces such as Object Linking and Embedding (OLE) developed by Microsoft. Such interfaces can be used to facilitate creating a compound document, in which objects or data from different applications reside in a single document and such object or data may be manipulated in an environment similar to its native environment in which the objects or data are initially generated. This is possible because an application may be embedded within an object or data it creates and imported as an integrated object into a document operated by a different application so that the former application may be invoked to manipulate its object within the document when needed. For example, within a Microsoft Word document, one may incorporate a Microsoft Excel sheet embedded with the Microsoft Excel application. When the Word document is opened, one may invoke Microsoft Excel editing tool within the Word (for embedding) to process the incorporated Microsoft Excel spreadsheet.
In medical imaging, there is a similar need. A patient data processed in one application system such as a dedicated clinical application system (or a server based thereupon) may be imported into a different data processing environment and further being viewed and/or interactively manipulated using tools of the first application within the environment of the system to which the patient data is exported. As a specific example, a Computer-Aided Detection (CAD) system may process patient data to identify locations of suspicious regions for, e.g., tumors, and such identified locations may be exported, with possibly other associated data such as patient information and the original imaging data, to another medical imaging analysis application such as a Picture Archiving and Communication System (PACS) environment, which is physicians' routine reading environment. Within the PACS environment, the physicians may need to invoke the CAD application on the same patient data and to use the CAD system's interactive tools to further analyze the data.
Existing systems in medical imaging utilize certain commonly conformed standard in medical imaging such as Digital Imaging and Communication in Medicine (DICOM). To share images of different modalities, DICOM specifies how images should be stored and transferred. However, DICOM does not allow data to be embedded with application(s) that creates the data, making it difficult, if not impossible, to manipulate data created in one medical imaging system to be manipulated in its native environment in a different application system.
With the current technical limitations in medical imaging, to share the result data generated by an application among different medical imaging systems, there are two existing solutions. One is simply sending the result data created in a first application to a second application in a recognizable format such as DICOM for display in the second application and for manipulation using tools of the second application. With this solution, manipulation using data tools of the first application system in the environment of the second application system is not possible. The second solution is to integrate the first application system such as CAD system with the second application system such as PACS through some mutually defined APIs. In this case, implementing the API-based integration requires code-level engineering effort, which can be not only time consuming but also cost prohibitive. For example, considering the complexity of CAD systems and PACS systems on today's market, the effort to achieve such API-based integration can be very costly. This kind of integration is especially difficult if one considers integration with systems already installed in a clinical environment. Other dedicated clinical applications, such as 3D visualization, have similar restrictions in their accessibility within another independent system.